Triple
T35986697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hennenman |
E1040729
|
entity |
| Predicate | municipalDistrictCode |
P43726
|
FINISHED |
| Object | DC18 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: DC18 | Statement: [Hennenman, municipalDistrictCode, DC18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: municipalDistrictCode Context triple: [Hennenman, municipalDistrictCode, DC18]
-
A.
hasCityDistrictCode
Indicates that a city district is associated with a specific identifying code.
-
B.
districtCode
chosen
Indicates that an entity is associated with, or identified by, a specific administrative district code.
-
C.
hasMunicipalDistrictNumber
Indicates that a municipality or local administrative unit is assigned a specific district number within its municipal structure.
-
D.
governmentalDistrictOf
Indicates that a governmental district is the administrative district to which a given entity belongs or in which it is located.
-
E.
municipalCodeSystem
Indicates a system that defines, organizes, or standardizes codes or regulations used by a municipality.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76e28293c8190ae3f4e2208b87117 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.